Quantitative susceptibility map reconstruction using annihilating filter-based low-rank Hankel matrix approach

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Purpose Quantitative susceptibility mapping (QSM) inevitably suffers from streaking artifacts caused by zeros on the conical surface of the dipole kernel in k-space. This work proposes a novel and accurate QSM reconstruction method based on k-space low-rank Hankel matrix constraint, avoiding the over-smoothing problem and streaking artifacts. Theory and Methods Based on the recent theory of annihilating filter-based low-rank Hankel matrix approach (ALOHA), QSM is formulated as deconvolution under low-rank Hankel matrix constraint in the k-space. The computational complexity and the high memory burden were reduced by successive reconstruction of 2-D planes along 3 independent axes of the 3-D phase image in Fourier domain. Feasibility of the proposed method was tested on a simulated phantom and human data and were compared with existing QSM reconstruction methods. Results The proposed ALOHA-QSM effectively reduced streaking artifacts and accurately estimated susceptibility values in deep gray matter structures, compared to the existing QSM methods. Conclusions The suggested ALOHA-QSM algorithm successfully solves the 3-dimensional QSM dipole inversion problem using k-space low rank property with no anatomical constraint. ALOHA-QSM can provide detailed brain structures and accurate susceptibility values with no streaking artifacts.
Publisher
WILEY
Issue Date
2020-03
Language
English
Article Type
Article
Citation

MAGNETIC RESONANCE IN MEDICINE, v.83, no.3, pp.858 - 871

ISSN
0740-3194
DOI
10.1002/mrm.27976
URI
http://hdl.handle.net/10203/270006
Appears in Collection
BiS-Journal Papers(저널논문)
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